Pattern Matching Applications Research Articles

Application of Approximate Pattern Matching in Two Dimensional Spaces to Grid Layout for Biochemical Network Maps

BackgroundFor visualizing large-scale biochemical network maps, it is important to calculate the coordinates of molecular nodes quickly and to enhance the understanding or traceability of them. The grid layout is effective in drawing compact, orderly, balanced network maps with node label spaces, but existing grid layout algorithms often require a high computational cost because they have to consider complicated positional constraints through the entire optimization process.ResultsWe propose a hybrid grid layout algorithm that consists of a non-grid, fast layout (preprocessor) algorithm and an approximate pattern matching algorithm that distributes the resultant preprocessed nodes on square grid points. To demonstrate the feasibility of the hybrid layout algorithm, it is characterized in terms of the calculation time, numbers of edge-edge and node-edge crossings, relative edge lengths, and F-measures. The proposed algorithm achieves outstanding performances compared with other existing grid layouts.Conclusions Use of an approximate pattern matching algorithm quickly redistributes the laid-out nodes by fast, non-grid algorithms on the square grid points, while preserving the topological relationships among the nodes. The proposed algorithm is a novel use of the pattern matching, thereby providing a breakthrough for grid layout. This application program can be freely downloaded from http://www.cadlive.jp/hybridlayout/hybridlayout.html.

Power-Efficient Cross-Correlation Beat Detection in Electrocardiogram Analysis Using Bitstreams

In this paper, we present a novel cross-correlator chip suitable for "smart" ECG electrodes. Sophisticated QRS-detection is feasible exploring multicomponent-based cross-correlation and by exploiting the simplicity offered by bitstream processing. The chip is evaluated using real ECG signals as an example application. Power-efficient running cross correlation is obtained with novel asynchronous circuit solutions consuming approximately 730 μ W while processing ECG data sampled at a rate of 250 Hz. The implemented generic cross-correlator may be explored for other pattern-matching applications in wireless sensor networks or other low-power applications.

CORRELATION BASED FACE MATCHING IN COMBINED GLOBAL AND LOCAL PRESERVING FEATURE SPACE

Face recognition plays a vital role in authentication, monitoring, indexing, access control and other surveillance applications. Much research on face recognition with various feature based approaches using global or local features employing a number of similarity measurement techniques have been done earlier. Feature based approaches using global features can effectively preserve only the Euclidean structure of face space, that suffer from lack of local features which may play a major role in some applications. On the other hand, wtih local features only the face subspace that best detects the essential face manifold structure is obtained and it also suffers loss in global features which may also be important in some other applications. Measuring similarity or distance between two feature vectors is also a key step for any pattern matching application. In this work, a new combined approach for recognizing faces that integrates the advantages of the global feature extraction technique by Linear Discriminant Analysis (LDA) and the local feature extraction technique by Locality Preserving Projections (LPP) with correlation based similarity measurement technique has been discussed. This has been validated by performing various experiments and by making a fair comparison with conventional methods.

Design of New Logic Architectures Utilizing Optimized Suspended-Gate Single-Electron Transistors

The operation and performances of the suspended-gate single-electron transistor (SET) are investigated through simulation. The movable gate is 3-D optimized, so that low actuation voltage (0.4 V), fast switching (1 ns), and ultralow pull-in energy (0.015 fJ) are simulated. A two-state capacitor model based on the 3-D results is then embedded with a SET analytical model in a SPICE environment to investigate the operation of the device. Through the control of the Coulomb oscillation characteristics, the position of the movable gate enables a background charge insensitive coding of the information. New circuit architectures with applications in cellular nonlinear network and pattern matching are also proposed and simulated.

Seeded Tree Alignment

The optimal transformation of one tree into another by means of elementary edit operations is an important algorithmic problem that has several interesting applications to computational biology. Here we introduce a constrained form of this problem in which a partial mapping of a set of nodes (the "seeds") in one tree to a corresponding set of nodes in the other tree is given, and present efficient algorithms for both ordered and unordered trees. Whereas ordered tree matching based on seeded nodes has applications in pattern matching of RNA structures, unordered tree matching based on seeded nodes has applications in co-speciation and phylogeny reconciliation. The latter involves the solution of the planar tanglegram layout problem, for which a polynomial-time algorithm is given here.

Property matching and weighted matching

In many pattern matching applications the text has some properties attached to its various parts. Pattern Matching with Properties (Property Matching, for short), involves a string matching between the pattern and the text, and the requirement that the text part satisfies some property. Some immediate examples come from molecular biology where it has long been a practice to consider special areas in the genome by their structures. It is straightforward to do sequential matching in a text with properties. However, indexing in a text with properties becomes difficult if we desire the time to be output dependent. We present an algorithm for indexing a text with properties in O ( n log | Σ | + n log log n ) time for preprocessing and O ( | P | log | Σ | + tocc π ) per query, where n is the length of the text, P is the sought pattern, Σ is the alphabet, and tocc π is the number of occurrences of the pattern that satisfy some property π . As a practical use of Property Matching we show how to solve Weighted Matching problems using techniques from Property Matching. Weighted sequences have recently been introduced as a tool to handle a set of sequences that are not identical but have many local similarities. The weighted sequence is a “statistical image” of this set, where we are given the probability of every symbol’s occurrence at every text location. Weighted matching problems are pattern matching problems where the given text is weighted. We present a reduction from Weighted Matching to Property Matching that allows off-the-shelf solutions to numerous weighted matching problems including indexing, swapped matching, parameterized matching, approximate matching, and many more. Assuming that one seeks the occurrence of pattern P with probability ϵ in weighted text T of length n , we reduce the problem to a property matching problem of pattern P in text T ′ of length O ( n ( 1 ϵ ) 2 log 1 ϵ ) .

Condition monitoring of linear guideways using a matched wavelet approach

The success of discrete wavelet methods for pattern matching applications can be significantly increased by finding a wavelet that closely approximates the pattern of interest. However, the process of fitting a wavelet to a given pattern is non-linear and non-trivial. In this paper we will address two problems. First, we develop and analyze an analytic approach for constructing a family of discrete wavelets that is optimally fitted to a given pattern. The construction is based on computing a suitable lifting filter. Secondly, we apply this matched wavelet approach to detect defects in linear guideways. Results with real data from acoustic measurements of such defects illustrate the potential of this approach.

Scale-Space Image Analysis Based on Hermite Polynomials Theory

The Hermite transform allows to locally approximate an image by a linear combination of polynomials. For a given scale ? and position ?, the polynomial coefficients are closely related to the differential jet (set of partial derivatives of the blurred image) for the same scale and position. By making use of a classical formula due to Mehler (late 19th century), we establish a linear relationship linking the differential jets at two different scales ? and positions ? involving Hermite polynomials. For multi-dimensional images, anisotropic excursions in scale-space can be handled in this way. Pattern registration and matching applications are suggested. We introduce a Gaussian windowed correlation function K (?) for locally matching two images. When taking the mutual translation parameter ? as an independent variable, we express the Hermite coefficients of K (?)interms of the Hermite coefficients of the two images being matched. This new result bears similarity with the Wiener-Khinchin theorem which links the Fourier transform of the conventional (flat-windowed) correlation function with the Fourier spectra of the images being correlated. Compared to the conventional correlation function, ours is more suited for matching localized image features. Numerical simulations using 2D test images illustrate the potentials of our proposals for signal and image matching in terms of accuracy and algorithmic complexity.

Space efficient linear time construction of suffix arrays

We present a linear time algorithm to sort all the suffixes of a string over a large alphabet of integers. The sorted order of suffixes of a string is also called suffix array, a data structure introduced by Manber and Myers that has numerous applications in pattern matching, string processing, and computational biology. Though the suffix tree of a string can be constructed in linear time and the sorted order of suffixes derived from it, a direct algorithm for suffix sorting is of great interest due to the space requirements of suffix trees. Our result is one of the first linear time suffix array construction algorithms, which improve upon the previously known O ( n log n ) time direct algorithms for suffix sorting. It can also be used to derive a different linear time construction algorithm for suffix trees. Apart from being simple and applicable for alphabets not necessarily of fixed size, this method of constructing suffix trees is more space efficient.

Kangaroo – A pattern-matching program for biological sequences

BackgroundBiologists are often interested in performing a simple database search to identify proteins or genes that contain a well-defined sequence pattern. Many databases do not provide straightforward or readily available query tools to perform simple searches, such as identifying transcription binding sites, protein motifs, or repetitive DNA sequences. However, in many cases simple pattern-matching searches can reveal a wealth of information. We present in this paper a regular expression pattern-matching tool that was used to identify short repetitive DNA sequences in human coding regions for the purpose of identifying potential mutation sites in mismatch repair deficient cells.ResultsKangaroo is a web-based regular expression pattern-matching program that can search for patterns in DNA, protein, or coding region sequences in ten different organisms. The program is implemented to facilitate a wide range of queries with no restriction on the length or complexity of the query expression. The program is accessible on the web at http://bioinfo.mshri.on.ca/kangaroo/ and the source code is freely distributed at http://sourceforge.net/projects/slritools/.ConclusionA low-level simple pattern-matching application can prove to be a useful tool in many research settings. For example, Kangaroo was used to identify potential genetic targets in a human colorectal cancer variant that is characterized by a high frequency of mutations in coding regions containing mononucleotide repeats.

Simple Optimal Parallel Multiple Pattern Matching

In this paper, we present a simple algorithm for solving the multipattern matching problem, with optimal speedup. The best-known deterministic parallel algorithm for this problem also provides optimal speedup, but relies crucially on a sophisticated construction of an automaton. Since then, Rabin has introduced a simple and elegant parallel algorithm (M. Rabin, in “Sequences '91: Methods in Communication, Security, and Computer Science,” Springer-Verlag, New York/Berlin, 1993). This is a Monte-carlo algorithm based on finger-print functions and it, too, has optimal speedup. Our algorithm simultaneously achieves the goals of optimal speedup of the deterministic algorithm, as well as the simplicity of the randomized Monte-carlo design cited above. Our algorithm presented here can also be extended to solve the multidimensional pattern-matching problem, also with optimal speedup. Interestingly, the sequential version of the algorithm derived by slowing down our parallel design yields a new and simple (linear-time) algorithm for string matching. It is distinguished by its lack of dependence on failure-functions and its related automata-theoretic variants, periodicities, or special data structures, but essentially uses a carefully constructed divide-and-conquer approach. This approach is systematized by us into the shrink-and-spawn technique, with a range of applications in parallel string and pattern matching in a paper that appears in S. Muthukrishnan and K. Palem (in “Proceedings 5th ACM Symp. on Parallel Algorithms and Architectures, 1993,” pp. 69–78).

Neural network based pattern matching application to power system signal processing

Neural network based pattern matching application to power system signal processing

Orientation Analysis by Computer-Aided Diffraction Pattern Matching in The TEM

Electron diffraction patterns taken in transmission electron microscopes are widely used for phase identification and orientation determination of crystallites as small as hundreds or even tens of nanometers in size. The analyses typically require rather tedious measurement of the patterns, and matching of calculated d-spacings and angles with those of known phases. Recently, the analysis of these patterns has been facilitated by powerful desktop computer programs that use digitally captured images for on-line measurement and simulation matching of" the diffraction spot and Kikuchi line patterns. This presentation will illustrate an application of computer-aided pattern simulation and matching for precise determination of crystal orientations.Two experimental TV camera arrangements were used to record diffraction patterns in a TEM. These included a cooled-CCD camera located on the electron optical axis below the microscope viewing chamber, and a simple TV-rate CCD that recorded directly from the inclined fluorescent viewing screen of the microscope.

An Application of Point Pattern Matching in Astronautics

We consider a point pattern matching problem occuring in astronautics: Given are pictures from a camera of unknown orientation, showing a section of the starry sky. We want to determine the orientation of the camera by matching the constellations in the pictures with a star catalogue. This problem occurs for satellite attitude determination with star field sensors. We present a new solution, which uses incremental Delaunay triangulation.

Application of Pattern Matching to Monitoring of Cutting Conditions in Milling. 1st Report, Fundamental Considerations.

In this study, we monitor dynamic cutting torque and surface roughness and apply several pattern-matching techniques to detect chipping and tool breakage in milling. This paper describes the following points : (1) in one cutting operation we make a difference between (n) th and (n + 1) th dynamic cutting torque and compare its standard deviation with the surface roughness ; (2) we apply the DP (dynamic programing) -matching technique and check the resemblance between each dynamic cutting torque and template pattern. Finally, experiments show good performance of these monitoring techniques.

A system for pattern matching applications on biosequences.

ANREP is a system for finding matches to patterns composed of (i) spacing constraints called 'spacers', and (ii) approximate matches to 'motifs' that are, recursively, patterns composed of 'atomic' symbols. A user specifies such patterns via a declarative, free-format and strongly typed language called A that is presented here in a tutorial style through a series of progressively more complex examples. The sample patterns are for protein and DNA sequences, the application domain for which ANREP was specifically created. ANREP provides a unified framework for almost all previously proposed biosequence patterns and extends them by providing approximate matching, a feature heretofore unavailable except for the limited case of individual sequences. The performance of ANREP is discussed and an appendix gives a concise specification of syntax and semantics. A portable C software package implementing ANREP is available via anonymous remote file transfer.

Parallel architecture overview

An increasing number of parallel computer products are appearing in the market place. Their design motivations and market areas cover a broad spectrum: (i) Transaction Processing Systems, such as Parallel UNIX systems (e.g. SEQUENT Balance), for data processing applications; (ii) Numeric Supercomputers, such as Hypercube systems (e.g. INTEL iPSC), for scientific and engineering applications; (iii) VLSI Architectures, such as parallel microcomputers (e.g. INMOS Transputer), for exploiting very large scales of integration; (iv) High-Level Language Computers, such as Logic machines (e.g. FUJITSU Kabu-Wake), for symbolic computation; and (v) Neurocomputers, such as Connectionist computers (e.g. THINKING MACHINES Connection Machine), for general-purpose pattern matching applications. This survey paper gives an overview of these novel parallel computers and discusses the likely commercial impact of parallel computers.

A finite state machine algorithm for finding restriction sites and other pattern matching applications

Existing algorithms for finding restriction endonuclease recognition sites use brute-force algorithms which run in time 0(NM) where N is the number of nucleotides in the sequence under analysis and M is the total number of nucleotides in all the different sites being searched for. This paper presents a deterministic finite state machine algorithm which runs in time 0(N). Memory use can be as high as 0(M4) but a slight modification to the basic algorithm can impose a theoretical upper bound of 0(M) at the cost of some added complexity in the execution of the state machine. The algorithm can operate with a single pass through the sequence under analysis, with no need to back up or (for non-circular sequences) store more than a single input character at a time. This type of algorithm can be adapted to many pattern-matching tasks and is simple enough to implement in hardware that it could, for example, be built into a disk controller as part of a specialized database machine.

Fast search techniques for use in vector quantisation and related pattern matching applications

Two techniques for the design and fast search of a vector quantiser codebook are proposed. These classify speech data vectors according to (i) the sign and (ii) the slope between successive samples. With both techniques the performance obtained is superior to that obtained from a conventional gain/shape vector quantiser and comparable to that of a full search vector quantiser. A major attraction of both approaches is that they significantly reduce the number of computations required for the codebook search.

Bit-sequential array for pattern matching

This letter presents the design and analysis of a bit-sequential array for pattern matching applications. The architecture makes multiple use of each data sample, has built-in concurrency and pipelining, and is based on a highly modular design with only nearest neighbor connections between array modules. The array computes all occurrences of a pattern of length m, in the string of length n, in O(m + n) time and O(m) hardware. The pattern and the string are fed in sequentially and the match indicators come out in the same fashion, leading to a significant reduction in silicon area.